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Machine Learning in Research Libraries: A Snapshot of Projects, Opportunities and Challenges

Home / Project Briefing Pages / CNI Fall 2019 Project Briefings / Machine Learning in Research Libraries: A Snapshot of Projects, Opportunities and Challenges

January 3, 2020

Harish Maringanti
Associate Dean for IT & Digital Library Services
University of Utah

Elizabeth Lorang
Interim Associate Dean, University Libraries; Associate Professor and Humanities Librarian
University of Nebraska-Lincoln

Zheng (John) Wang
Associate University Librarian, Digital Access, Resources, and Information Technology; Interim Director, Navari Family Center for Digital Scholarship
University of Notre Dame

Adoption of machine learning (ML) in cultural heritage organizations and research libraries is broadening, and will only continue to grow, be it for gaining internal efficiencies via automating collections processing or enhancing access and discovery experiences for users. Over the last several years, each of our teams has been exploring a range of practical and theoretical questions related to the intersection of machine learning and libraries. In this presentation, project leaders will discuss their efforts and outline opportunities and complexities in using machine learning in research libraries.

Presentation

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Filed Under: CNI Fall 2019 Project Briefings, Emerging Technologies, Project Briefing Pages
Tagged With: cni2019fall, Project Briefings & Plenary Sessions

Last updated:  Monday, February 24th, 2020

 

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